Lei Shi

International Conference on Artificial Neural Networks · with Chen · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Lei Shi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Hans-Peter Kriegel

Papers from Lei Shi's perspective

Ordered by how strongly the researchers Lei Shi trusts endorse each paper. Same corpus, a different order for every researcher.

1. GENERATIVE ADVERSARIAL NETS
2. Improved Techniques for Training GANs
3. Generative Moment Matching Networks
4. Feature bagging for outlier detection (Knowledge Discovery and Data Mining)
5. LOF: identifying density-based local outliers
6. MMD GAN: Towards Deeper Understanding of Moment Matching Network
7. Data Mining: Concepts and Techniques
8. Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection (International Conference on Learning Representations)
9. SWaT: a water treatment testbed for research and training on ICS security (2016 International Workshop on Cyber-physical Systems for Smart Water Networks (CySWater))
10. Angle-based outlier detection in high-dimensional data (Knowledge Discovery and Data Mining)

Their papers

• MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks (2019) — 1,053 citations